使用 plotly 绘制 geopandas 数据框

问题描述

我有一个 geopandas 数据框，它由区域名称 (District)、geometry 列和 amount 列组成.我的目标是使用下面提到的方法绘制等值线图

我还检查了我的列的格式/类型是否正确.

这是我用来绘制地图的代码

fig = px.choropleth(合并,geojson=merged.geometry,位置=合并的.index，颜色=金额")fig.update_geos(fitbounds="locations", visible=False)图.show()

它产生了下图

这显然不是正确的数字.由于某些原因，它不显示地图，而是显示一条线，当我放大时，我能够看到地图，但它有线穿过它.像这样

有没有人遇到过类似的问题?如果是这样，您是如何解决的?

我使用的 Plotly 版本是 4.7.0.我已尝试升级到最新版本，但仍然无法正常工作.

非常感谢任何帮助.请在我的

I have a geopandas dataframe, which consists of the region name(District), the geometry column, and the amount column. My goal is to plot a choropleth map using the method mentioned below https://plotly.com/python/choropleth-maps/#using-geopandas-data-frames

Here’s a snippet of my dataframe

I also checked that my columns were in the right format/type.

And here's the code I used to plot the map

fig = px.choropleth(merged,

                   geojson=merged.geometry,

                   locations=merged.index,

                   color="Amount")

fig.update_geos(fitbounds="locations", visible=False)

fig.show()

It produced the below figure

which is obviously not the right figure. For some reasons, it doesn't show the map, instead it shows a line and when I zoom in, I am able to see the map but it has lines running through it. Like this

Has anyone ran into a similar problem? If so how were you able to resolve it?

The Plotly version I am using is 4.7.0. I have tried upgrading to a most recent version but it still didn’t work.

Any help is greatly appreciated. Please find my code and the data on my github.

解决方案

I'll give you the answer to @tgrandje's comment that solved the problem. Thanks to @Poopah and @tgrandje for the opportunity to raise the answer.

import pandas as pd
import plotly.express as px
import geopandas as gpd
import pyproj

# reading in the shapefile
fp = "./data/"
map_df = gpd.read_file(fp)
map_df.to_crs(pyproj.CRS.from_epsg(4326), inplace=True)

df = pd.read_csv("./data/loans_amount.csv")
# join the geodataframe with the cleaned up csv dataframe
merged = map_df.set_index('District').join(df.set_index('District'))
#merged = merged.reset_index()
merged.head()

fig = px.choropleth(merged, geojson=merged.geometry, locations=merged.index, color="Amount")
fig.update_geos(fitbounds="locations", visible=False)

fig.show()